Forrester
Research names Google Cloud a Leader in Data Management for
Analytics

Gain insights with real-time and
predictive analytics

Query streaming data in real time and get up-to-date
information on all your business processes. Predict
business outcomes easily with built-in machine learning
and without the need to move data.

Access data and share insights
with ease

Securely access and share analytical insights in your
organization with a few clicks. Easily create stunning
reports and dashboards using popular business intelligence
tools, out of the box.

Protect your data and operate
with trust

Rely on BigQuery’s robust security, governance, and
reliability controls that offer high availability and a
99.9% uptime SLA. Data is encrypted by default including
support for customer-managed encryption keys.

Key features

BigQuery ML

BigQuery ML
enables data scientists and data analysts to build and
operationalize ML models on planet-scale structured or
semi-structured data, directly inside BigQuery, using
simple SQL—in a fraction of the time. Export BigQuery ML
models for online prediction into Cloud AI Platform or
your own serving layer. Learn more about the
models we currently support.

BigQuery BI Engine

BigQuery BI Engine
is a blazing-fast in-memory analysis service for BigQuery
that allows users to analyze large and complex datasets
interactively with sub-second query response time and high
concurrency. BigQuery BI Engine seamlessly integrates with
familiar tools like
Data Studio
and will help accelerate data exploration and analysis for
Looker,
Sheets, and our BI partners in the coming months.

BigQuery GIS

BigQuery GIS
uniquely combines the serverless architecture of BigQuery
with native support for geospatial analysis, so you can
augment your analytics workflows with location
intelligence. Simplify your analyses, see spatial data in
fresh ways, and unlock entirely new lines of business with
support for arbitrary points, lines, polygons, and
multi-polygons in common geospatial data formats.

Use cases

Use case

Migrating data
from Teradata

Migrate your on-premises legacy data warehouse to an agile,
cloud-based data warehouse solution. The combination of
BigQuery Data Transfer Service (DTS) and a special
on-premises migration agent lets you copy data to BigQuery,
from a legacy warehouse such as Teradata.

And you can monitor recurring data loads to BigQuery by
using BigQuery DTS’s web UI. We also provide additional
easy-to-use tools and a global partner support system.
Learn more.

Google Cloud basics

Migrating data warehouses to BigQuery

Part one in a series that
helps you transition from an on-premises data
warehouse to BigQuery on Google Cloud.

Teradata migration details and options

The BigQuery Data Transfer Service allows you to copy your
data from an Amazon Redshift data warehouse to BigQuery. The
service will engage migration agents in Google Kubernetes
Engine and trigger an unload operation from Amazon Redshift
to a staging area in an Amazon S3 bucket. Then the BigQuery
Data Transfer Service transfers your data from the Amazon S3
bucket to BigQuery.

Google Cloud basics

Introduction to BigQuery Data Transfer Service

Overview of the BigQuery
Data Transfer Service that automates data movement
into BigQuery on a scheduled, managed basis.

Migrating data warehouses to BigQuery: Data pipelines

All features

Serverless

With serverless data
warehousing, Google does all resource provisioning
behind the scenes, so you can focus on data and
analysis rather than worrying about upgrading,
securing, or managing the infrastructure.

Real-time analytics

BigQuery’s high-speed
streaming insertion API provides a powerful
foundation for real-time analytics, making your
latest business data immediately available for
analysis. You can also leverage Pub/Sub and Dataflow
to stream data into BigQuery.

Automatic high availability

BigQuery transparently
and automatically provides highly durable,
replicated storage in multiple locations and high
availability with no extra charge and no additional
setup.

Standard SQL

BigQuery supports a
standard SQL dialect that is ANSI:2011 compliant,
which reduces the need for code rewrites. BigQuery
also provides ODBC and JDBC drivers at no cost to
ensure your current applications can interact with
its powerful engine.

Federated query and logical data warehousing

Through powerful
federated queries, BigQuery can process external
data sources in object storage (Cloud Storage) for
Parquet and ORC open source file formats,
transactional databases (Bigtable, Cloud SQL), or
spreadsheets in Drive. All this can be done without
moving the data.

Convergence of data warehouse and data lake

Run open source data
science workloads (Spark, TensorFlow, Dataflow and
Apache Beam, MapReduce, Pandas and scikit-learn)
directly on BigQuery using the Storage API. The
Storage API provides a much simpler architecture and
less data movement, and doesn't need to have
multiple copies of the same data.

Materialized Views

Accelerate query
performance and reduce costs within your environment
with BigQuery Materialized Views. It is easy to set
up, effortless to use, and best of all it's real
time, allowing you to quickly get answers to your
questions.

Storage and compute separation

With BigQuery’s
separated storage and compute, you have the option
to choose the storage and processing solutions that
make sense for your business and control access and
costs for each.

Automatic backup and easy restore

BigQuery automatically
replicates data and keeps a seven-day history of
changes, allowing you to easily restore and compare
data from different times.

Geospatial data types and functions

BigQuery GIS brings SQL
support for arbitrary points, lines, polygons, and
multi-polygons in WKT and GeoJSON format. You can
simplify your geospatial analyses, see your
location-based data in new ways, or unlock entirely
new lines of business.

Data transfer service

The
BigQuery Data Transfer Service
automatically transfers data from external data
sources, like Google Marketing Platform, Google Ads,
YouTube, and partner SaaS applications to BigQuery
on a scheduled and fully managed basis. Users can
also easily transfer data from Teradata and Amazon
S3 to BigQuery.

Big data ecosystem integration

With Dataproc and
Dataflow, BigQuery provides integration with the
Apache big data ecosystem, allowing existing
Hadoop/Spark and Beam workloads to read or write
data directly from BigQuery using the Storage
API.

Petabyte scale

Get great performance on
your data, while knowing you can scale seamlessly to
store and analyze petabytes to exabytes of data with
ease.

Flexible pricing models

On-demand pricing lets
you pay only for the storage and compute that you
use. Flat-rate pricing with Reservations enables
high-volume users or enterprises to choose price
predictability and workload management seamlessly.
For more information, see
BigQuery pricing
or
cost controls.

Data governance and security

BigQuery provides strong
security and governance controls with fine-grained
Identity and Access Management,
and your data is always encrypted at rest and in
transit.

Geo-expansion

BigQuery gives you the
option of geographic data control (in US, Asia, and
European locations), without the headaches of
setting up and managing clusters and other computing
resources in-region.

Foundation for AI

Besides bringing ML to
your data with
BigQuery ML,
integrations with AI Platform Prediction and
TensorFlow enable you to train powerful models on
structured data in minutes with just SQL.

Automatically move data
from hundreds of popular business SaaS applications
into BigQuery for free with Data Transfer Service
(DTS) or leverage data integration tools like Cloud
Data Fusion, Informatica, Talend, and more. Load and
transform data at any scale from hybrid and
multi-cloud applications.

Programmatic interaction

BigQuery provides a REST
API for easy programmatic access and application
integration. Client libraries are available in Java,
Python, Node.js, C#, Go, Ruby, and PHP. Business
users can use Google Apps Script to access BigQuery
from Sheets.

Rich monitoring and logging

BigQuery provides rich
monitoring, logging, and alerting through
Cloud Audit Logs
and it can serve as a repository for logs from any
application or service using Cloud Logging.

Public datasets

Google Cloud
Public Datasets
offer a powerful data repository of more than 100
high-demand public datasets from different
industries. Google provides free storage for all
public datasets, and customers can query up to 1 TB
of data per month at no cost.

Commercial datasets

Commercial data providers
host their data offerings directly in BigQuery and
Cloud Storage, which means that once you license a
dataset from one of our partners, you can access
this data immediately and process it in place
without having to store or move any data.